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Logical XOR function.
tf.math.logical_xor(
    x, y, name='LogicalXor'
)
x ^ y = (x | y) & ~(x & y)
Requires that x and y have the same shape or have
broadcast-compatible
shapes. For example, x and y can be:
- Two single elements of type bool
- One tf.Tensorof typebooland one singlebool, where the result will be calculated by applying logical XOR with the single element to each element in the larger Tensor.
- Two tf.Tensorobjects of typeboolof the same shape. In this case, the result will be the element-wise logical XOR of the two input tensors.
Usage:
a = tf.constant([True])b = tf.constant([False])tf.math.logical_xor(a, b)<tf.Tensor: shape=(1,), dtype=bool, numpy=array([ True])>
c = tf.constant([True])x = tf.constant([False, True, True, False])tf.math.logical_xor(c, x)<tf.Tensor: shape=(4,), dtype=bool, numpy=array([ True, False, False, True])>
y = tf.constant([False, False, True, True])z = tf.constant([False, True, False, True])tf.math.logical_xor(y, z)<tf.Tensor: shape=(4,), dtype=bool, numpy=array([False, True, True, False])>
| Args | |
|---|---|
| x | A tf.Tensortype bool. | 
| y | A tf.Tensorof type bool. | 
| name | A name for the operation (optional). | 
| Returns | |
|---|---|
| A tf.Tensorof type bool with the same size as that of x or y. |